The present invention relates to projection imaging systems in general and cell classification, and more particularly, to high throughput automated systems using projection imaging, such as flow optical tomography (FOT), for detecting cancer in high risk individuals based on highly quantitative measurements of nuclear or cytoplasmic molecular marker compartmentalization associated with malignancy and disease.
The most common method of diagnosing cancer in patients is by obtaining a sample of the suspect tissue and examining it under a microscope for the presence of obviously malignant cells. While this process is relatively easy when the anatomic location of the suspect tissue is known and can be sampled thoroughly (e.g. the uterine cervix), it is not so easy when there is no readily identifiable tumor or lesion and the area to be sampled is very large. For example, with reference to the detection of lung cancer, it is not possible to swab the entire airway of the lungs. A sample such as sputum must be used as it contains cells exfoliated from the air passages in the lungs. This creates a dilution problem because an early lung cancer is very small compared to the entire internal surface of the lungs and, as a result, the number of cells shed from the tumor is also very small relative to that of normal cells. The problem is compounded because only a small portion of the sputum sample is actually examined. Thus, detection of lung cancer with traditional sputum cytology requires one or more relatively rare cancer cells to be present in the portion of the sample that is examined. Therefore, if the sample does not perceptively and accurately reflect the conditions of the lung, then patients having lung cancer may not be diagnosed properly.
One example of a microscope-based system and method for detecting diagnostic cells and cells having malignancy-associated changes is disclosed in Palcic et al., U.S. Pat. No. 6,026,174. The Palcic et al. system includes an automated classifier having a conventional microscope, camera, image digitizer, a computer system for controlling and interfacing these components, a primary classifier for initial cell classification, and a secondary classifier for subsequent cell classification. The method utilizes the automated classifier to automatically detect diagnostic cells and cells having malignancy-associated changes. This method improves on traditional cytology by detecting cells exhibiting malignancy-associated changes, which are more common than cancer cells. However, the quality of the diagnostic result is limited by the use of a conventional microscope, which does not permit accurate measurement of stain densities. Furthermore, the method of Palcic et al. does not address the use of specific molecular probes nor the compartmentalization of molecular markers.
With the advent of specific molecular probes, such as antibodies and nucleic acid probes, new disease related questions can be addressed by tagging these molecular probes and then measuring their location and concentration within biological cells and tissues. The use of tagged, specific molecular probes enable the indirect quantitation and compartmentalization of molecular markers such as pRb, p53/p53 binding protein 1 (53BP1), Sam68, PTEN, E2F and 5-methylcytosine-guanine (methyl CpG) which may be informative of disease processes such as cancer. (See, for example, Pasquale, D., xe2x80x9cRetinoblastoma Protein Tethered to Promoter DNA Represses TBP-Mediated Transcriptionxe2x80x9d, Journal of Cellular Biochemistry, 70:281-287, 1998, Rappold I, xe2x80x9cTumor Suppressor p53 Binding Protein 1 (53BP1) Is Involved in DNA Damage-signaling Pathwaysxe2x80x9d, The Journal of Cell Biology, 153 (3):613-620. 2001, Chen, T., xe2x80x9cA Role for the GSG Domain in Localizing Sam68 to Novel Nuclear Structures in Cancer Cell Linesxe2x80x9d, Molecular Biology of the Cell 10:3015-3033, 1999, Perren, A., xe2x80x9cMutation and Expression Analyses Reveal Differential Subcellular Compartmentalization of PTEN in Endocrine Pancreatic Tumors Compared to Normal Islet Cellsxe2x80x9d, American Journal of Pathology, 157 (4):1097-1103, 2000, Gil, R., xe2x80x9cSubcellular Compartmentalization of E2F Family Members Is Required for Maintenance of the Postmitotic State in Terminally Differentiated Musclexe2x80x9d, The Journal of Cell Biology, 148(6): 1187-1201, 2000, Rountree, M., xe2x80x9cDNA methylation, chromatin inheritance, and cancerxe2x80x9d, Oncogene , 20:3156-3165, 2001). As the need to more accurately localize and quantify these probes is emerging, there is a concomitant need for improved techniques to measure probe densities with submicron resolution in two dimensions (2D) and three dimensions (3D). Conventional light microscopy, which utilizes cells mounted on glass slides, can only approximate 2D density measurements because of limitations in focal plane depth, sampling angles, and problems with cell preparations that typically cause cells to overlap in the plane of the image. Another drawback of light microscopy is the inherent limitation of viewing through an objective lens where only the area within the narrow focal plane provides accurate data for analysis.
Flow cytometry methods generally overcome the cell overlap problem by causing cells to flow one-by-one in a fluid stream. Unfortunately, flow cytometry systems do not generate images of cells of the same quality as traditional light microscopy, and, in any case, the images are not three-dimensional. For background, those skilled in the art are directed to Shapiro, H M, Practical Flow Cytometry, 3rd ed., Wiley-Liss, 1995.
Confocal microscopy offers 3D imaging of samples by imaging successive thin layers of the sample to create a stack of 2D images, which can be viewed in 3D. The imaging is accomplished by scanning a narrow spot of light across the sample on a glass slide. Fluorescent or reflected light is focused onto a detector through a pinhole, which blocks out-of-focus light from impinging on the detector. Thus, the size of the pinhole determines the resolution in the vertical direction and the spot size determines the resolution in the horizontal directions. Unfortunately, confocal microscopy is a very slow procedure because the image is built up by scanning a small spot of light in a raster across the sample and the sample has to be rescanned to produce each additional slice. Another drawback is that cells deposited on slides are flattened, causing distortions of cellular structures.
In the area of computer aided tomography, U.S. Pat. No. 5,402,460, issued Mar. 28, 1995, to Johnson, et al. entitled xe2x80x9cThree-dimensional Microtomographic Analysis Systemxe2x80x9d discloses a microtomographic system for generating high-resolution, three-dimensional images of a specimen using an x-ray generator and an x-ray detector that measures the attenuation of the x-ray beam through the specimen. Two projections, each using a different energy x-ray beam, of each view of the specimen are made with Johnson, et al.""s microtomographic system. After the two projections of one view of the specimen are made, the specimen is rotated on the specimen holder and another set of projections is made. The projections of each view of the specimen are analyzed together to provide a quantitative indication of the phase fraction of the material comprising the specimen. The projections of the different views are combined to provide a three-dimensional image of the specimen. U.S. Pat. No. 5,402,460 is incorporated herein by reference. Although the x-ray technology as taught by U.S. Pat. No. 5,402,460 is useful for some applications, it does not provide an optical solution useful for flow cytometry, whereby one could measure the 3D distribution of molecular density within a biological cell.
To overcome the aforementioned limitations and others found in such systems, it is a motivation of this invention to combine the one-by-one cell presentation of flow cytometry with computational optical tomography from multiple point source projections to reconstruct density information within a cell from a plurality of projections. The reconstructed density information enables the accurate quantitation of specifically labeled markers and the compartmentalization of such markers.
The density information referred to herein is unique to projection imaging systems that do not require the use of lenses and focal planes with their inherent unwanted blur artifact due to unfocussed structures outside the narrow focal plane. Because projection imaging systems do not require lenses and focal planes, but rather, produce shadowgrams wherein all structures are in clear focus all at once, the measurement of density features will be more quantitative and accurate than in conventional microscopy systems. Moreover, 3D reconstruction from the projection images enables the separation of features that may overlap in any single 2D view. These density features are directly related to the locations and quantities of the molecular probes used to stain the cells.
The present invention overcomes deficiencies of the prior art wherein measurement of subcellular or subnuclear compartmentalization of molecular markers was not used in diagnostics because, until now, no efficient method to perform these measurements existed.
In one embodiment, the present invention provides a method for detecting cells associated with malignancy in a cell sample, comprising the steps of obtaining a cell sample and suspending the cells in a solution; if required, fixing the cells of the cell sample in suspension; staining and/or labeling the cells to generate optical densities associated with specific molecular markers or other structures within each cell of the sample; generating a flow stream of single cells; illuminating each cell in the flow stream with a xe2x80x9cpointxe2x80x9d source of light and obtaining one or more projection images (e.g. shadowgrams) through the cell with a digital detector; compensating the projection images for variations in background illumination; analyzing the projection images to detect and compartmentalize the specifically labeled molecular markers; providing the marker compartmentalization and other analytical data to at least one classifier that identifies and characterizes cells associated with malignancy in the cell sample.
In another aspect, the present invention provides a system for automatically detecting molecular markers and compartmentalization or localization of the markers in cells. The preferred system includes a flow optical tomography (FOT) instrument that is controlled by and interfaced with a computer system. Projection images captured by the FOT are stored and manipulated by the computer system to detect the presence of labeled molecular markers. Multiple projection images can be reconstructed by the computer to generate three-dimensional (3D) images to compartmentalize the labeled markers within the cells or nuclei as well as quantifying such markers.
To determine molecular marker compartmentalization, a cell sample is obtained and stained in suspension, and then imaged by the FOT. The stain or tagged probe is specific for molecular markers of interest, including but not limited to pRb, p53/53BP1, E2F, PTEN, SAM68 and methyl CpG. The molecular probe can be tagged with chromophores, fluorochromes or enzymes that can generate chromophores or fluorochromes. The computer system then analyzes the projection images directly and/or computes the 3D reconstruction that is also analyzed. The images are corrected for nonuniformillumination and other imperfections of the image acquisition system. After all images are corrected, the edges, surfaces and volumes and densities of the objects of interest are calculated, i.e., the boundary that determines which pixels or voxels belong to the object or structure of interest and which belong to the background. These objects of interest include aggregates of tagged probes and stained cellular structures.
The computer system then calculates a set of 1D, 2D and 3D feature values for each object or structure. For some feature calculations, the boundary along the highest gradient value is corrected by either dilating or eroding the edge (or surface) by one or more pixels (or voxels). This is done such that each feature achieves a greater discriminating power between classes of objects and is thus object specific. These feature values are then analyzed by a classifier that uses the feature values to determine whether the object is an artifact or an object or structure of interest within a cell or nucleus that had been specifically stained or labeled. If the object appears to be an object or structure of interest, then the feature values are further analyzed by the classifier to determine whether the object is of the type and in a cellular or nuclear compartment indicative of disease. Once an object or structure of interset has been identified, the associated molecular probe density is assigned to that particular object thus achieving the compartmentalization of the probe. Based on the number of cells found in the sample that appear to have significant disease related changes in marker compartmentalization, a statistical determination can be made of whether the patient from whom the cell sample was obtained is healthy or harbors a malignant growth.
In other embodiments, the present invention provides a method for detecting epithelial cells in a cell sample and a method for detecting cells with molecular compartmentalization that is correlated with disease among the epithelial cells. In another embodiment, a method for predicting whether a patient will develop cancer is provided.